The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

We review a model of computation used in industrial practice in signal processing software environments and experimentally and other contexts. We give this model the name "dataflow process networks," and study its formal properties as well as its utility as a basis for programming language design. Variants of this model are used in commercial visual programming systems such as SPW from the Alta Group of Cadence (formerly Comdisco Systems), COSSAP from Synopsys (formerly Cadis), the DSP Station from Mentor Graphics, and Hypersignal from Hyperception. They are also used in research software such as Khoros from the University of New Mexico and Ptolemy from the University of California at Berkeley, among many others. Dataflow process networks are shown to be a special case of Kahn process networks, a model of computation where a number of concurrent processes communicate through unidirectional FIFO channels, where writes to the channel are nonblocking, and reads are blocking. In dataflow process networks, each process consists of repeated "firings" of a dataflow "actor." An actor defines a (often functional) quantum of computation. By dividing processes into actor firings, the considerable overhead of context switching incurred in most implementations of Kahn process networks is avoided. We relate dataflow process networks to other dataflow models, including those used in dataflow machines, such as static dataflow and the tagged-token model. We also relate dataflow process networks to functional languages such as Haskell, and show that modern language concepts such as higher-order functions and polymorphism can be used effectively in dataflow process networks. A number of programming examples using a visual syntax are given. >

/pdf/dataflow-process-networks-3mdwy0uhx2.pdf

Dataflow process networks

The rapid uptake of mobile devices and the rising popularity of mobile applications and services pose unprecedented demands on mobile and wireless networking infrastructure. Upcoming 5G systems are evolving to support exploding mobile traffic volumes, real-time extraction of fine-grained analytics, and agile management of network resources, so as to maximize user experience. Fulfilling these tasks is challenging, as mobile environments are increasingly complex, heterogeneous, and evolving. One potential solution is to resort to advanced machine learning techniques, in order to help manage the rise in data volumes and algorithm-driven applications. The recent success of deep learning underpins new and powerful tools that tackle problems in this space. In this paper, we bridge the gap between deep learning and mobile and wireless networking research, by presenting a comprehensive survey of the crossovers between the two areas. We first briefly introduce essential background and state-of-the-art in deep learning techniques with potential applications to networking. We then discuss several techniques and platforms that facilitate the efficient deployment of deep learning onto mobile systems. Subsequently, we provide an encyclopedic review of mobile and wireless networking research based on deep learning, which we categorize by different domains. Drawing from our experience, we discuss how to tailor deep learning to mobile environments. We complete this survey by pinpointing current challenges and open future directions for research.

/pdf/deep-learning-in-mobile-and-wireless-networking-a-survey-ct8cy2kuqi.pdf

Deep Learning in Mobile and Wireless Networking: A Survey

Objects. The ~ b s t rac t ~ b j ect forms the fundamental base class for the entire design and all other classes are derived from this base class. The Abstract Object class defines and characterizes all the essential properties every class in this 404 OBJECT-ORIENTED SIMULATION

Handbook of Simulation

Network lifetime has become the key characteristic for evaluating sensor networks in an application-specific way. Especially the availability of nodes, the sensor coverage, and the connectivity have been included in discussions on network lifetime. Even quality of service measures can be reduced to lifetime considerations. A great number of algorithms and methods were proposed to increase the lifetime of a sensor network—while their evaluations were always based on a particular definition of network lifetime. Motivated by the great differences in existing definitions of sensor network lifetime that are used in relevant publications, we reviewed the state of the art in lifetime definitions, their differences, advantages, and limitations. This survey was the starting point for our work towards a generic definition of sensor network lifetime for use in analytic evaluations as well as in simulation models—focusing on a formal and concise definition of accumulated network lifetime and total network lifetime. Our definition incorporates the components of existing lifetime definitions, and introduces some additional measures. One new concept is the ability to express the service disruption tolerance of a network. Another new concept is the notion of time-integration: in many cases, it is sufficient if a requirement is fulfilled over a certain period of time, instead of at every point in time. In addition, we combine coverage and connectivity to form a single requirement called connected coverage. We show that connected coverage is different from requiring noncombined coverage and connectivity. Finally, our definition also supports the concept of graceful degradation by providing means of estimating the degree of compliance with the application requirements. We demonstrate the applicability of our definition based on the surveyed lifetime definitions as well as using some example scenarios to explain the various aspects influencing sensor network lifetime.

/pdf/on-the-lifetime-of-wireless-sensor-networks-59hdyqoqi3.pdf

On the lifetime of wireless sensor networks

Practical models for energy-efficient prefetching in mobile embedded systems

Performance studies of the EM-4 multithreaded multiprocessor on nonnumeric problems: preliminary report

As multithreaded server applications and runtime systems prevail, garbage collection is becoming an essential feature to support high performance systems. The fundamental issue of garbage collector (GC) design is to maximize the recycled space with minimal time overhead. This paper proposes two innovative solutions: one to improve space efficiency, and the other to improve time efficiency. To achieve space efficiency, we propose the Space Tuner that utilizes the novel concept of allocation speed to reduce wasted space. Conventional static space partitioning techniques often lead to inefficient space utilization. The Space Tuner adjusts the heap partitioning dynamically such that when a collection is triggered, all space partitions are fully filled. To achieve time efficiency, we propose a novel parallelization method that reduces the compacting GC parallelization problem into a tree traversal parallelization problem. This method can be applied for both normal and large object compaction. Object compaction is hard to parallelize due to strong data dependencies such that the source object can not be moved to its target location until the object originally in the target location has been moved out. Our proposed algorithm overcomes the difficulties by dividing the heap into equal-sized blocks and parallelizing the movement of the independent blocks. It is noteworthy that these proposed algorithms are generic such that they can be utilized in different GC designs.

/pdf/space-and-time-efficient-garbage-collectors-for-parallel-1f30unli27.pdf

Space-and-time efficient garbage collectors for parallel systems

In this paper, we analyze the time complexity and performance of a heuristic for code partitioning for Distributed Memory Multiprocessors (DMMs). The partitioning method is data-flow based where all levels of parallelism are exploited. Given a weighted Directed Acyclic Graph (DAG) representation of the program, our algorithm automatically determines the granularity of parallelism by partitioning the graph into tasks to be scheduled on the DMM. The granularity of parallelism depends only on the program to be executed and on the target machine parameters. The output of our algorithm is passed on as input to the scheduling phase. Finding an optimal solution to this problem is NP-complete. Due to the high cost of graph algorithms, it is nearly impossible to come up with close to optimal solutions that do not have very high cost (higher order polynomial). Our proposed heuristic gives good performance and has relatively low cost.

Analysis of a Heuristic for Code Partitioning

E-commerce has evolved with the digital technology revolution over the years. Last-mile logistics service contributes a significant part of the e-commerce experience. In contrast to the traditional last-mile logistics services, smart logistics service with autonomous driving technologies provides a promising solution to reduce the delivery cost and to improve efficiency. However, the traffic conditions in complex traffic environments, such as those in China, are more challenging compared to those in well-developed countries. Many types of moving objects (such as pedestrians, bicycles, electric bicycles, and motorcycles, etc.) share the road with autonomous vehicles, and their behaviors are not easy to track and predict. This paper introduces a technical solution from this http URL, a leading E-commerce company in China, to the autonomous last-mile delivery in complex traffic environments. Concretely, the methodologies in each module of our autonomous vehicles are presented, together with safety guarantee strategies. Up to this point, this http URL has deployed more than 300 self-driving vehicles for trial operations in tens of provinces of China, with an accumulated 715,819 miles and up to millions of on-road testing hours.

Jean-Luc Gaudiot

Papers

Practical models for energy-efficient prefetching in mobile embedded systems

Performance studies of the EM-4 multithreaded multiprocessor on nonnumeric problems: preliminary report

Space-and-time efficient garbage collectors for parallel systems

Analysis of a Heuristic for Code Partitioning

Autonomous Last-mile Delivery Vehicles in Complex Traffic Environments